Skip to main content

Main menu

  • Home
  • Articles
    • Current Issue
    • Next in The JI
    • Archive
    • Brief Reviews
      • Neuroimmunology: To Sense and Protect
    • Pillars of Immunology
    • Translating Immunology
    • Most Read
    • Top Downloads
    • Annual Meeting Abstracts
  • COVID-19/SARS/MERS Articles
  • Info
    • About the Journal
    • For Authors
    • Journal Policies
    • Influence Statement
    • For Advertisers
  • Editors
  • Submit
    • Submit a Manuscript
    • Instructions for Authors
    • Journal Policies
  • Subscribe
    • Journal Subscriptions
    • Email Alerts
    • RSS Feeds
    • ImmunoCasts
  • More
    • Most Read
    • Most Cited
    • ImmunoCasts
    • AAI Disclaimer
    • Feedback
    • Help
    • Accessibility Statement
  • Other Publications
    • American Association of Immunologists
    • ImmunoHorizons

User menu

  • Subscribe
  • Log in

Search

  • Advanced search
The Journal of Immunology
  • Other Publications
    • American Association of Immunologists
    • ImmunoHorizons
  • Subscribe
  • Log in
The Journal of Immunology

Advanced Search

  • Home
  • Articles
    • Current Issue
    • Next in The JI
    • Archive
    • Brief Reviews
    • Pillars of Immunology
    • Translating Immunology
    • Most Read
    • Top Downloads
    • Annual Meeting Abstracts
  • COVID-19/SARS/MERS Articles
  • Info
    • About the Journal
    • For Authors
    • Journal Policies
    • Influence Statement
    • For Advertisers
  • Editors
  • Submit
    • Submit a Manuscript
    • Instructions for Authors
    • Journal Policies
  • Subscribe
    • Journal Subscriptions
    • Email Alerts
    • RSS Feeds
    • ImmunoCasts
  • More
    • Most Read
    • Most Cited
    • ImmunoCasts
    • AAI Disclaimer
    • Feedback
    • Help
    • Accessibility Statement
  • Follow The Journal of Immunology on Twitter
  • Follow The Journal of Immunology on RSS

Antigen Recognition in the Islets Changes with Progression of Autoimmune Islet Infiltration

Robin S. Lindsay, Kaitlin Corbin, Ashley Mahne, Bonnie E. Levitt, Matthew J. Gebert, Eric J. Wigton, Brenda J. Bradley, Kathryn Haskins, Jordan Jacobelli, Qizhi Tang, Matthew F. Krummel and Rachel S. Friedman
J Immunol January 15, 2015, 194 (2) 522-530; DOI: https://doi.org/10.4049/jimmunol.1400626
Robin S. Lindsay
*Department of Biomedical Research, National Jewish Health, Denver, CO 80206;
†Department of Immunology and Microbiology, University of Colorado School of Medicine, Denver, CO 80206;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Kaitlin Corbin
‡Department of Pathology, University of California San Francisco, San Francisco, CA 94143; and
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Ashley Mahne
§Department of Surgery, University of California San Francisco, San Francisco, CA 94143
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Bonnie E. Levitt
*Department of Biomedical Research, National Jewish Health, Denver, CO 80206;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Matthew J. Gebert
*Department of Biomedical Research, National Jewish Health, Denver, CO 80206;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Eric J. Wigton
*Department of Biomedical Research, National Jewish Health, Denver, CO 80206;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Brenda J. Bradley
*Department of Biomedical Research, National Jewish Health, Denver, CO 80206;
†Department of Immunology and Microbiology, University of Colorado School of Medicine, Denver, CO 80206;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Kathryn Haskins
*Department of Biomedical Research, National Jewish Health, Denver, CO 80206;
†Department of Immunology and Microbiology, University of Colorado School of Medicine, Denver, CO 80206;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Jordan Jacobelli
*Department of Biomedical Research, National Jewish Health, Denver, CO 80206;
†Department of Immunology and Microbiology, University of Colorado School of Medicine, Denver, CO 80206;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Qizhi Tang
§Department of Surgery, University of California San Francisco, San Francisco, CA 94143
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Matthew F. Krummel
‡Department of Pathology, University of California San Francisco, San Francisco, CA 94143; and
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Rachel S. Friedman
*Department of Biomedical Research, National Jewish Health, Denver, CO 80206;
†Department of Immunology and Microbiology, University of Colorado School of Medicine, Denver, CO 80206;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Article
  • Figures & Data
  • Info & Metrics
  • PDF + SI
  • PDF
Loading

Article Figures & Data

Figures

  • Additional Files
  • FIGURE 1.
    • Download figure
    • Open in new tab
    • Download powerpoint
    FIGURE 1.

    Intravital imaging maintains intact blood flow without damaging the pancreas. (A) Setup for intravital two-photon pancreas imaging. A heated suction window stabilizes the surgically exposed pancreas for imaging. (B and C) Representative maximum intensity projection images of islets imaged intravitally through the suction imaging window captured using two-photon microscopy. Vascular space is labeled with 70-kDa dextran-rhodamine (red). Images are representative of seven experiments. (B) Islets are identifiable by their dense convoluted vasculature compared with exocrine tissue vasculature. The border of the islet is identified with a yellow dashed line. Scale bar, 30 μm. (C) NOD mouse islet with transferred BDC-2.5 T cells (green). The collagen fluorescence is provided by the second harmonic (blue), which demonstrates that the T cell infiltration is inside the islet basement membrane. Scale bar, 100 μm. (D) Neutrophils do not accumulate at the site of imaging. Fluorescently labeled neutrophils were transferred into mice prior to surgical exposure and imaging of the pancreas through the suction window. The number of neutrophils was counted every 90 s. The lack of neutrophil accumulation shows that the imaging site was not damaged during imaging. Data are representative of one islet per mouse in three experiments. (E) Suction imaging window does not impede blood flow. Fluorescent beads were tracked within blood vessels of different diameter within and around the pancreatic islets. Each dot represents one bead. Data are representative of three islets per mouse in two experiments.

  • FIGURE 2.
    • Download figure
    • Open in new tab
    • Download powerpoint
    FIGURE 2.

    Explanted islet imaging allows high resolution, high throughput imaging. (A) Setup of explanted islet two-photon imaging. Isolated pancreatic islets were mounted in low melting temperature agarose and maintained at 35–37°C with constant flow of oxygenated media. (B) Representative multiple field image of explanted islets. BDC-2.5 T cells (red) were transferred into WT NOD recipients, and islets were isolated. Image shows a maximum intensity projection of explanted islets. Nuclei are labeled with Hoechst 33342 (blue). Scale bar, 200 μm. Images are representative of >3 experiments.

  • FIGURE 3.
    • Download figure
    • Open in new tab
    • Download powerpoint
    FIGURE 3.

    T cell motility increases with progression of islet infiltration. (A and B) Activated BDC-2.5 T cells (green) were fluorescently labeled and transferred 24 h prior to imaging. Representative maximum intensity projection images from explanted (A) or intravital (B) islets captured using two-photon microscopy. Dashed lines represent the islet border. Green lines represent 10-min paths of BDC-2.5 T cell movement. Images are representative of islets with mild infiltration (<30% of islet volume infiltrated) or advanced infiltration (30–60% of islet volume infiltrated). Scale bars, 50 μm. (C–E) Quantification of T cell motility within explanted or intravital islets. Data pooled from 16 explanted islets from four mice in three independent experiments and 16 intravital islets from seven mice in seven independent experiments. *p < 0.05, measured by Student t test. (C) Linear correlation of the average T cell velocity within an islet versus the percentage of the infiltrated islet volume. Each dot represents the average of all of the tracked T cells within a single islet. (D and E) Average of individual islets. (D) T cell crawling speed in explanted versus intravital islets. (E) Fold increase in crawling speed between islets with mild and advanced infiltration.

  • FIGURE 4.
    • Download figure
    • Open in new tab
    • Download powerpoint
    FIGURE 4.

    T cells reduce arrest and increase displacement as islet infiltration progresses. Activated BDC-2.5 T cells were fluorescently labeled and transferred 24 h prior to imaging, as in Fig. 3. Data were pooled from 16 explanted islets from four mice in three independent experiments and 16 intravital islets from seven mice in seven independent experiments. (A and B) Average of individual islets. (A) T cell track straightness (1 = cell moves in a straight line). (B and C) T cell arrest coefficient (% of time crawling speed is <2 μm/min). (D) Mean squared displacement (μm2) over time. *p < 0.05, **p < 0.01, ***p < 0.001; measured by two-way ANOVA with Bonferroni posttests or Student t test.

  • FIGURE 5.
    • Download figure
    • Open in new tab
    • Download powerpoint
    FIGURE 5.

    Early T cell arrest is Ag dependent. BDC-2.5 T cells were fluorescently labeled and transferred into WT NOD or NOD.C6 recipient mice 48 h prior to imaging to determine infiltration state. BDC-6.9 T cells and BDC-2.5 T cells were cotransferred 24 h prior to imaging to determine T cell motility. The Ag for BDC-6.9 T cells is absent in the NOD.C6 recipients. Data represent 25 WT islets from four mice in four experiments and 25 NOD.C6 islets from five mice in five experiments. Each point represents the average T cell motility within one islet. (A) In WT NOD islets in which the Ag was present for BDC-2.5 and BDC-6.9 T cells, both types of T cells increase motility at a similar rate as islet infiltration increases. (B) In NOD.C6 islets, in which the Ag is present for BDC-2.5 T cells, but absent for BDC-6.9 T cells, the BDC-6.9 T cells move faster in the absence of their Ag. (C) The ratio of average BDC-6.9 T cell motility to the average BDC-2.5 T cell motility within the same islet. Infiltration states: very mild (0–5%), mild (5–30%), and advanced (30–60%). (D) Comparison of the arrest coefficient of all BDC-2.5 and BDC-6.9 T cells within islets with mild infiltration. BDC-6.9 T cells (No Ag) have reduced arrest. *p < 0.05, **p < 0.01, ***p < 0.001 by two-tailed Student t test.

  • FIGURE 6.
    • Download figure
    • Open in new tab
    • Download powerpoint
    FIGURE 6.

    Sustained T cell–CD11c+ APC interactions are lost with progression of islet infiltration. Fluorescently labeled BDC-2.5 T cells were transferred into CD11c-YFP hosts 24 h prior to islet isolation and imaging. Data represent 15 islets from five mice in five independent experiments. (A and B) Maximum intensity projection images showing BDC-2.5 (red) and CD11c+ APCs (green) within pancreatic islets. Yellow box indicates the region shown in time-lapse images on the right. Gray circles highlight the CD11c+ APCs that the T cell of interest has contacted; yellow arrows show current T cell–APC contacts. Time stamps = min:s. (A) Sustained T cell–APC interaction in an islet with mild infiltration. Scale bar, 40 μm for whole islet and 10 μm for time-lapse images. (B) Transient T cell contacts with different CD11c+ APCs in an islet with advanced infiltration. Scale bar, 50 μm for whole islet and 20 μm for time-lapse images. (C) Average percentage of T cells within individual islets that contact CD11c+ APCs for at least 2 min. (D) Average percentage of T cells that contacted CD11c+ APCs, which had sustained interactions of ≥10 min. (E) Duration of T cell– CD11c+ APC contacts. *p < 0.001, ***p < 0.001 by two-tailed Student t test.

Additional Files

  • Figures
  • Data Supplement

    Files in this Data Supplement:

    • Supplemental Material 1 (PDF)
    • Supplemental Video 1 (MPG)
    • Supplemental Video 2 (MPG)
    • Supplemental Video 3 (MPG)
    • Supplemental Video 4 (MPG)
    • Supplemental Video 5 (MPG)
    • Supplemental Video 6 (MPG)
    • Supplemental Video 7 (MPG)
    • Supplemental Video 8 (MPG)
PreviousNext
Back to top

In this issue

The Journal of Immunology: 194 (2)
The Journal of Immunology
Vol. 194, Issue 2
15 Jan 2015
  • Table of Contents
  • Table of Contents (PDF)
  • About the Cover
  • Advertising (PDF)
  • Back Matter (PDF)
  • Editorial Board (PDF)
  • Front Matter (PDF)
Print
Download PDF
Article Alerts
Sign In to Email Alerts with your Email Address
Email Article

Thank you for your interest in spreading the word about The Journal of Immunology.

NOTE: We only request your email address so that the person you are recommending the page to knows that you wanted them to see it, and that it is not junk mail. We do not capture any email address.

Enter multiple addresses on separate lines or separate them with commas.
Antigen Recognition in the Islets Changes with Progression of Autoimmune Islet Infiltration
(Your Name) has forwarded a page to you from The Journal of Immunology
(Your Name) thought you would like to see this page from the The Journal of Immunology web site.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Citation Tools
Antigen Recognition in the Islets Changes with Progression of Autoimmune Islet Infiltration
Robin S. Lindsay, Kaitlin Corbin, Ashley Mahne, Bonnie E. Levitt, Matthew J. Gebert, Eric J. Wigton, Brenda J. Bradley, Kathryn Haskins, Jordan Jacobelli, Qizhi Tang, Matthew F. Krummel, Rachel S. Friedman
The Journal of Immunology January 15, 2015, 194 (2) 522-530; DOI: 10.4049/jimmunol.1400626

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Share
Antigen Recognition in the Islets Changes with Progression of Autoimmune Islet Infiltration
Robin S. Lindsay, Kaitlin Corbin, Ashley Mahne, Bonnie E. Levitt, Matthew J. Gebert, Eric J. Wigton, Brenda J. Bradley, Kathryn Haskins, Jordan Jacobelli, Qizhi Tang, Matthew F. Krummel, Rachel S. Friedman
The Journal of Immunology January 15, 2015, 194 (2) 522-530; DOI: 10.4049/jimmunol.1400626
del.icio.us logo Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google logo Mendeley logo
  • Tweet Widget
  • Facebook Like

Jump to section

  • Article
    • Abstract
    • Introduction
    • Materials and Methods
    • Results
    • Discussion
    • Disclosures
    • Acknowledgments
    • Footnotes
    • References
  • Figures & Data
  • Info & Metrics
  • PDF + SI
  • PDF

Related Articles

Cited By...

More in this TOC Section

  • SZB120 Exhibits Immunomodulatory Effects by Targeting eIF2α to Suppress Th17 Cell Differentiation
  • Gut Commensal Segmented Filamentous Bacteria Fine-Tune T Follicular Regulatory Cells to Modify the Severity of Systemic Autoimmune Arthritis
  • A Functionally Distinct CXCR3+/IFN-γ+/IL-10+ Subset Defines Disease-Suppressive Myelin-Specific CD8 T Cells
Show more AUTOIMMUNITY

Similar Articles

Navigate

  • Home
  • Current Issue
  • Next in The JI
  • Archive
  • Brief Reviews
  • Pillars of Immunology
  • Translating Immunology

For Authors

  • Submit a Manuscript
  • Instructions for Authors
  • About the Journal
  • Journal Policies
  • Editors

General Information

  • Advertisers
  • Subscribers
  • Rights and Permissions
  • Accessibility Statement
  • Public Access
  • Privacy Policy
  • Disclaimer

Journal Services

  • Email Alerts
  • RSS Feeds
  • ImmunoCasts
  • Twitter

Copyright © 2021 by The American Association of Immunologists, Inc.

Print ISSN 0022-1767        Online ISSN 1550-6606